Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add xujingchen1996/research-app-toolkit --skill cv-polishgit clone --depth 1 https://github.com/xujingchen1996/research-app-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xujingchen1996/research-app-toolkit/cv-polish)<a href="https://agentmods.dev/skills/xujingchen1996/research-app-toolkit/cv-polish"><img src="https://agentmods.dev/badge/skills/xujingchen1996/research-app-toolkit/cv-polish/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xujingchen1996/research-app-toolkit/cv-polish"><img src="https://agentmods.dev/badge/skills/xujingchen1996/research-app-toolkit/cv-polish.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.00583 |
| Opus 5 | $0.00026 | $0.00292 |
| Sonnet 5 | $0.00011 | $0.00117 |
| Haiku 4.5 | $0.00005 | $0.00058 |
Grade A, and why
cv-polish scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CV Refinement
Preconditions
- Read
../../memory.mdfirst. - If
cv_profile_analyzedis nottrue, or## CV Profileis basically empty, first suggest that the user runcv-analyze, unless the user explicitly asks you to rebuild the profile directly from the current CV.
Language Rules
- Support three output modes:
zh,en, andbilingual. - If the user explicitly specifies the output language or target CV language, prioritize the user's specification.
- Otherwise read
preferred_languagefrommemory.md. - If it is still unclear, default to following the user's current conversation language.
- If the user requests bilingual output, prioritize one main version plus a short counterpart note, rather than mechanically repeating every line twice.
Fill In the Key Information First
If any of the following is missing, ask concise questions in Chinese to fill it in:
- target program / school / degree
- which 1 to 2 experiences should be emphasized
- target research direction
- desired output language
Working Method
- Read the original CV:
- Prefer the
cv_file_pathrecorded inmemory.md - If it is missing, then confirm the path with the user
- Prefer the
- Review it from the following dimensions:
- whether the structural order fits research-oriented applications
- whether the bullets use clear verbs and explicit outcomes
- whether research-related experience is placed early enough
- whether common research-application elements are missing, such as publications, research experience, methods, or technical stack
- Make targeted refinements based on the target program:
- strengthen the experiences most relevant to the target direction
- adjust section order
- add necessary keywords, but do not invent experiences
- Decide the delivery mode based on the source file type:
- if it is a text-based source file, it can be edited directly
- if it is a format such as PDF / DOCX that is not suitable for stable direct rewriting, default to section-by-section rewriting suggestions and a copyable new version
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 59 lines · 53 tokens per session scan A eba277c5e31e
cv-polish is a skill published in the GitHub repository xujingchen1996/research-app-toolkit (115 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 583 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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